Cheryl A. Murphy

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology

To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future.

Adverse outcome pathways and ecological risk assessment: Bridging to population‐level effects

Maintaining the viability of populations of plants and animals is a key focus for environmental regulation. Population-level responses integrate the cumulative effects of chemical stressors on individuals as those individuals interact with and are affected by their conspecifics, competitors, predators, prey, habitat, and other biotic and abiotic factors. Models of population-level effects of contaminants can integrate information from lower levels of biological organization and feed that information into higher-level community and ecosystem models. As individual-level endpoints are used to predict population responses, this requires that biological responses at lower levels of organization be translated into a form that is usable by the population modeler. In the current study, we describe how mechanistic data, as captured in adverse outcome pathways (AOPs), can be translated into modeling focused on population-level risk assessments. First, we describe the regulatory context surrounding population modeling, risk assessment and the emerging role of AOPs. Then we present a succinct overview of different approaches to population modeling and discuss the types of data needed for these models. We describe how different key biological processes measured at the level of the individual serve as the linkage, or bridge, between AOPs and predictions of population status, including consideration of community-level interactions and genetic adaptation. Several case examples illustrate the potential for use of AOPs in population modeling and predictive ecotoxicology. Finally, we make recommendations for focusing toxicity studies to produce the quantitative data needed to define AOPs and to facilitate their incorporation into population modeling.

Evidence for harvest-induced maternal influences on the reproductive rates of fish populations

Knowledge of the relationship between the number of offspring produced (recruitment) and adult abundance is fundamental to forecasting the dynamics of an exploited population. Although small-scale experiments have documented the importance of maternal quality to offspring survival in plants and animals, the effects of this association on the recruitment dynamics of exploited populations are largely unknown. Here, we present results from both a simple population model and a meta-analysis of time-series data from 25 species of exploited marine fishes that suggest that a population of older, larger individuals has a higher maximum reproductive rate than an equivalent population of younger, smaller individuals, and that this difference increases with the reproductive lifespan of the population. These findings (i) establish an empirical link between population age structure and reproductive rate that is consistent with strong effects of maternal quality on population dynamics and (ii) provide further evidence that extended age structure is essential to the sustainability of many exploited fish stocks.

Putative steroidal pheromones in the round goby, Neogobius melanostomus: olfactory and behavioral responses.

To identify potential hormonal pheromones of the round goby (Neogobius melanostomus), a species recently introduced to the Great Lakes, we used electro-olfactogram (EOG) recording to examine olfactory responsiveness to more than 100 steroids and prostaglandins. Neogobius detected free and conjugated 18-, 19and 21-carbon steroids, but did not detect prostaglandins. EOG cross-adaptation, used to determine if Neogobius can discriminate the detected compounds at the sensory level, suggested that the detected steroids act on four classes of olfactory receptor mechanisms named (according to the most potent ligand for each): estrone, 17β-estradiol-3β-glucuronide, etiocholanolone, and dehydroepiandrosterone3-sulfate. Although none of the detected steroids induced reproductive behaviors, exposure to steroids from three of the four receptor classes (estrone, 17β-estradiol-3β-glucuronide, or etiocholanolone) increased ventilation rate in males, whereas only etiocholanolone increased ventilation rate in females. Using the ventilation increase as a behavioral bioassay of steroid detection, behavioral cross-adaptation studies in males demonstrated that steroids discriminated at the sensory level are also discriminated behaviorally. These findings suggest the round goby may use steroids as putative pheromones.

A genetic basis for the phenotypic differentiation between siscowet and lean lake trout (Salvelinus namaycush)

In Lake Superior there are three principal forms of lake trout (Salvelinus namaycush): lean, siscowet and humper. Wild lean and siscowet differ in the shape and relative size of the head, size of the fins, location and size of the eyes, caudal peduncle shape and lipid content of the musculature. To investigate the basis for these phenotypic differences, lean and siscowet lake trout, derived from gametes of wild populations in Lake Superior, were reared communally under identical environmental conditions for 2.5 years. Fish were analysed for growth, morphometry and lipid content, and differences in liver transcriptomics were investigated using Roche 454 GS‐FLX pyrosequencing. The results demonstrate that key phenotypic differences between wild lean and siscowet lake trout such as condition factor, morphometry and lipid levels, persist in these two forms when reared in the laboratory under identical environmental conditions. This strongly suggests that these differences are genetic and not a result of environmental plasticity. Transcriptomic analysis involving the comparison of hepatic gene frequencies (RNA‐seq) and expression (quantitative reverse transcription–polymerase chain reaction (qPCR)) between the two lake trout forms, indicated two primary gene groups that were differentially expressed; those involving lipid synthesis, metabolism and transport (acyl‐CoA desaturase, acyl‐CoA binding protein, peroxisome proliferator‐activated receptor gamma, and apolipoproteins), and those involved with immunity (complement component C3, proteasome, FK506 binding protein 5 and C1q proteins). The results demonstrate that RNA‐seq can be used to identify differentially expressed genes; however, some discrepancies between RNA‐seq analysis and qPCR indicate that methods for deep sequencing may need to be refined and/or different RNA‐seq platforms utilized.

Maternal influences on population dynamics: evidence from an exploited freshwater fish

We used a field experiment, population modeling, and an analysis of 30 years of data from walleye (Sander vitreus; a freshwater fish) in Lake Erie to show that maternal influences on offspring survival can affect population dynamics. We first demonstrate experimentally that the survival of juvenile walleye increases with egg size (and, to a lesser degree, female energy reserves). Because egg size in this species tends to increase with maternal age, we then model these maternal influences on offspring survival as a function of maternal age to show that adult age structure can affect the maximum rate at which a population can produce new adults. Consistent with this hypothesis, we present empirical evidence that the maximum reproductive rate of an exploited population of walleye was approximately twice as high when older females were abundant as compared to when they were relatively scarce. Taken together, these results indicate that age- or size-based maternal influences on offspring survival can be an important mechanism driving population dynamics and that exploited populations could benefit from management strategies that protect, rather than target, reproductively valuable individuals.

Toxicity of dietary methylmercury to fish: Derivation of ecologically meaningful threshold concentrations

Threshold concentrations associated with adverse effects of dietary exposure to methylmercury (MeHg) were derived from published results of laboratory studies on a variety of fish species. Adverse effects related to mortality were uncommon, whereas adverse effects related to growth occurred only at dietary MeHg concentrations exceeding 2.5 µg g(-1) wet weight. Adverse effects on behavior of fish had a wide range of effective dietary concentrations, but generally occurred above 0.5 µg g(-1) wet weight. In contrast, effects on reproduction and other subclinical endpoints occurred at dietary concentrations that were much lower (<0.2 µg g(-1) wet wt). Field studies generally lack information on dietary MeHg exposure, yet available data indicate that comparable adverse effects have been observed in wild fish in environments corresponding to high and low MeHg contamination of food webs and are in agreement with the threshold concentrations derived here from laboratory studies. These thresholds indicate that while differences in species sensitivity to MeHg exposure appear considerable, chronic dietary exposure to low concentrations of MeHg may have significant adverse effects on wild fish populations but remain little studied compared to concentrations in mammals or birds.

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: II. A focus on growth impairment in fish

Adverse outcome pathways (AOPs) organize knowledge on the progression of toxicity through levels of biological organization. By determining the linkages between toxicity events at different levels, AOPs lay the foundation for mechanism-based alternative testing approaches to hazard assessment. Here, we focus on growth impairment in fish to illustrate the initial stages in the process of AOP development for chronic toxicity outcomes. Growth is an apical endpoint commonly assessed in chronic toxicity tests for which a replacement is desirable. Based on several criteria, we identified reduction in food intake to be a suitable key event for initiation of middle-out AOP development. To start exploring the upstream and downstream links of this key event, we developed three AOP case studies, for pyrethroids, selective serotonin reuptake inhibitors (SSRIs) and cadmium. Our analysis showed that the effect of pyrethroids and SSRIs on food intake is strongly linked to growth impairment, while cadmium causes a reduction in growth due to increased metabolic demands rather than changes in food intake. Locomotion impairment by pyrethroids is strongly linked to their effects on food intake and growth, while for SSRIs their direct influence on appetite may play a more important role. We further discuss which alternative tests could be used to inform on the predictive key events identified in the case studies. In conclusion, our work demonstrates how the AOP concept can be used in practice to assess critically the knowledge available for specific chronic toxicity cases and to identify existing knowledge gaps and potential alternative tests.

Using Nested Models and Laboratory Data for Predicting Population Effects of Contaminants on Fish: A Step Toward a Bottom-Up Approach for Establishing Causality in Field Studies

Predicting the effects of contaminants on fish populations is difficult due to their complex life history and high interannual variation in their population abundances. We present an approach that extrapolates laboratory data on contaminant effects, including behavioral effects, to the population level by using a series of nested statistical and simulation models. The approach is illustrated using PCB effects on Atlantic croaker. Laboratory experiments were performed that estimated PCB effects on fecundity, egg mortality, and the swimming speed and predator evasion behavior of larvae. A statistical model converted impaired predator evasion to reduced probability of escaping a predatory fish. An individual-based model then converted the output of the statistical model into changes in larval stage duration and survival, which were used to change elements of the matrix model. A matrix projection model simulated population dynamics for 100 years for baseline conditions and for two hypothetical PCB exposure scenarios. PCB effects were imposed in the model by reducing the fecundity of exposed adults, increasing egg mortality, and increasing the larval stage duration and mortality rate. Predicted population effects of PCBs were small relative to the interannual variation. Our analysis is a step toward understanding population responses to stressors and for ultimately establishing causality in field situations.

Testing and applying a fish vitellogenesis model to evaluate laboratory and field biomarkers of endocrine disruption in Atlantic croaker (Micropogonias undulatus) exposed to hypoxia

Recently, hypoxia has been shown to act as an endocrine disruptor. We used a model of vitellogenesis in a female sciaenid fish to simulate the effects of hypoxia and to determine if reproductive impairment observed in field-caught fish could be attributed to dissolved oxygen conditions at the sampling sites. The model is a set of coupled, ordinary differential equations that simulate major biochemical reactions from the secretion of gonadotropin to production of vitellogenin. Various intermediate variables in the model correspond to commonly measured biomarkers, and we assume a direct relationship between cumulative vitellogenin (VTG) and the gonadosomatic index (GSI). Model predictions were compared to results of laboratory studies that examined the effects of hypoxia on Atlantic croaker (Micropogonias undulatus) reproduction. When hypoxia was assumed to cause reduced gonadotropin and impaired aromatase activity, model predictions of VTG production were similar to laboratory-measured reductions in GSI. The model was then applied to reproductive biomarkers measured in fish from normoxic and hypoxic locations in Pensacola Bay (FL, U.S.A.). We simulated the relationship between reduced estradiol-17beta and VTG production under hypoxia, and we compared these results with field data. Good agreement between field and simulation results suggested that croaker collected from hypoxic sites in October were exposed to hypoxic conditions for an extended period during gonadal recrudescence and that hypoxia was a dominant cause for the reduced GSIs. Monte Carlo uncertainty analyses suggested that the maximum rate of free testosterone production is the most sensitive parameter. Our simulations demonstrated that the model can be used identifying the mechanism underlying endocrine disruption and for interpreting field-measured biomarkers in situations of multiple stressors.